A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints. (15th November 2015)

• Record Type: Journal Article
• Authors: Koltsaklis, Nikolaos E.; Georgiadis, Michael C.
• Is Part Of: Applied energy. Volume 158(2015)
• Page Start: 310
• Page End: 331
• Publication Date: 2015-11-15
• Subjects: Mixed integer linear programming -- Unit commitment problem -- Long term energy planning -- Electricity markets -- CO2 emissions -- System marginal price; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2015.08.054
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A short-term structured investment planning model has been developed. Unit commitment problem is incorporated into the long-term planning horizon. Inherent intermittency of renewables is modelled in a comprehensive way. The impact of CO2 emission pricing in long-term investment decisions is quantified. The evolution of system's marginal price is evaluated for all the planning horizon. Abstract: This work presents a generic mixed integer linear programming (MILP) model that integrates the unit commitment problem (UCP), i.e., daily energy planning with the long-term generation expansion planning (GEP) framework. Typical daily constraints at an hourly level such as start-up and shut-down related decisions (start-up type, minimum up and down time, synchronization, soak and desynchronization time constraints), ramping limits, system reserve requirements are combined with representative yearly constraints such as power capacity additions, power generation bounds of each unit, peak reserve requirements, and energy policy issues (renewables penetration limits, CO2 emissions cap and pricing). For modelling purposes, a representative day (24 h) of each month over a number of years has been employed in order to determine the optimal capacity additions, electricity market clearing prices, and daily operational planning of the studied power system. The model has been tested on an illustrative case study of the Greek power system. Our approach aims to provide useful insight into strategic and challenging decisions to be determined by investors and/or policy makers at a national and/or regional level by providing the optimal energy roadmap under real operating and design constraints.